1. Field of the Invention
The present invention relates to an image processing apparatus having a function of gradation-conversion or grayscale-conversion processing for converting a number of bits, to an image processing method, and to a communication system.
2. Description of the Related Art
For example, in order to display an image having a pixel value of N bits on a display apparatus displaying images with a pixel value of M bits, where M is less than N, it is necessary to convert an N-bit image into an M-bit image, that is to say, to perform gradation conversion processing in order to convert image gradations.
As a method for converting grayscale from an N-bit image to an M-bit image, for example, there is a familiar method of quantization into M-bit pixel values by simply rounding down low-order N−M bits of N-bit pixel values.
In the gradation conversion using the quantization, for example, 8 bits allow 256 (=28) grayscales, but 4 bits allow only 16 (=24) grayscales.
Accordingly, in gradation conversion in which an 8-bit grayscale image is quantized into high-order 4 bits by rounding down low-order bits, banding, in which a change in grayscale appears as a band, occurs.
In order to prevent such banding and to express pseudo grayscales before gradation conversion has been performed in an image after gradation conversion, for example, there is a famous error diffusion method.
By the error diffusion method, for example, in an image of 16 grayscales obtained by gradation conversion of an image of 256 grayscales, 256 grayscales are visually expressed for a human eye using 16 grayscales.
That is to say, if low bits are simply rounded down, quantization errors become conspicuous in a displayed image, and thus it is difficult to maintain image quality.
Accordingly, a method of performing delta-sigma modulation on an image, in which such quantization errors are modulated to high-frequency bands in consideration of human visual characteristics, is famous as an error diffusion method.
In general, a two-dimensional filter filtering quantization errors is used for error diffusion.
For the two-dimensional filter, a filter of Jarvis, Judice&Ninke, and a filter of Floyd&Steinberg are familiar (For example, refer to written by Hitoshi KIYA, “Understandable Digital Image Processing”, ver. 6, CQ Publishing Co., Ltd., pp. 196-213, January 2000).